Reach On The Application Of Dynamic Uncertain Causality Graph (DUCG) For Training Plan Recommendation Of Strength And Conditioning In Male Badminton Players

"Empowering" physical training through big data and artificial intelligence is one of the crucial ways to solve the problem of China’s lack of high-level coaches and scientific researchers.Simultaneously,how to help our country’s grassroots coaches and physical coaches to use these training methods rationally when introducing new training methods in our country is also an urgent issue for our country to solve.This research uses the recommended application of Dynamic Uncertain Causality Graph(DUCG)in the physical training program of badminton men’s singles athletes as the research object.It aims to explore artificial intelligence and physical training to help coaches and physical coaches develop physical training programs.Take the men’s badminton event as an example,establishing a physical training action library,and recommend physical training programs for athletes under different levels and different states through the Dynamic Uncertain Causality Graph(DUCG)algorithm,in order to guide novice coaches in the development of relatively accurate training programs.Research is to comprehensively sort out the development of physical training,research the rules and lessons,and explore the development path of badminton physical training combined with artificial intelligence algorithm recommended training programs.Through the combination of physical training program formulation and Dynamic,Uncertain Causality Graph,in Strength and Conditioning training within the theoretical basis,combined with the experience input of national coaches,this is used as a recommendation basis to lay a foundation for exploring the development of the combination of artificial intelligence algorithms and physical training.This study uses the literature method to conduct a more comprehensive historical review and current research on developing physical training from the timeline.It studies the integration and promotion of other disciplines and physical training.It concludes that physical training is through The conclusion of continuous integration with other disciplines,and new developments have paved the way for developing physical fitness disciplines.At the same time,it expounds on the characteristics of badminton,the requirements of physical training and the existing grading standards of badminton physical fitness,combined with the application of the DUCG algorithm in auxiliary diagnosis to explore the fusion of the two.Through the questionnaire survey method,research shows that the algorithm recommended physical training program is a ’sports+artificial’ intelligence recommendation system that combines the basic principles of physical training,the experience of national coaches and artificial intelligence algorithms.The physical training program recommended by the DUCG algorithm can help novices Coaches formulate training programs that are closer to national team coaches,effectively increasing the probability of formulating physical training programs that are more suitable for athletes;at the same time,the recommendation system has the potential value in other projects.In future research,the recommendation algorithm’s action content can be increased and enriched,and in the recommendation process,the algorithm can make the next training program based on the previous training content.